Abstract-This paper discusses the problem of generating patrol paths for a team of mobile robots inside a designated target area. Patrolling requires an area to be visited repeatedly by the robot(s) in order to monitor its current state. First, we present frequency optimization criteria used for evaluation of patrol algorithms. We then present a patrol algorithm that guarantees maximal uniform frequency, i.e., each point in the target area is covered at the same optimal frequency. This solution is based on finding a circular path that visits all points in the area, while taking into account terrain directionality and velocity constraints. Robots are positioned uniformly along this path, using a second algorithm. Moreover, the solution is guaranteed to be robust in the sense that uniform frequency of the patrol is achieved as long as at least one robot works properly.

Abstract-This paper discusses the problem of generating patrol paths for a team of mobile robots inside a designated target area. Patrolling requires an area to be visited repeatedly by the robot(s) in order to monitor its current state. First, we present frequency optimization criteria used for evaluation of patrol algorithms. We then present a patrol algorithm that guarantees maximal uniform frequency, i.e., each point in the target area is covered at the same optimal frequency. This solution is based on finding a circular path that visits all points in the area, while taking into account terrain directionality and velocity constraints. Robots are positioned uniformly along this path, using a second algorithm. Moreover, the solution is guaranteed to be robust in the sense that uniform frequency of the patrol is achieved as long as at least one robot works properly.

Abstract-There is considerable interest in real-world formation-maintenance tasks, where robots move together while maintaining a geometric shape. This interest is motivated by promise of robustly and efficiently moving multiple robots along a path, guided by a human operator. This paper presents a comprehensive set of techniques that fulfill this promise: (i) a novel method for fusing open-and closed-loop controllers, for robust formation-maintenance; (ii) an ecological display, allowing a human operator to monitor and guide robots, while improving their performance and reducing the failure rate; and (iii) a set of methods for interacting with the formation in the case of a disconnect in the formation. We evaluate each of these contributions in extensive experiments, including 25 human operators. We show significant improvements in performance (in terms of movement time), robustness (both in number of failures, as well as failure rate), and consistency between operators.

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Summary. Many applications of robots require a human operator to supervise and operate multiple robots. In particular, the operator may be required to resolve call requests when robots require assistance. Previous investigations assume that robots are independent of each other, and allow the operator to resolve one request at a time. However, key challenges and opportunities arise when robots work in tightly-coordinating teams. Robots depend on each other, and thus a single failing robot may cause multiple call requests to be issued (by different robots). Moreover, when the operator switches control to a robot, its teammates must often wait idly until the call request is resolved. We contrast previous approaches with two novel distributed methods, where the call-request resolution is itself considered a collaborative problem-solving activity, and non-failing robots use their knowledge of the coordination to assist the operator. We empirically compare the different approaches in several scenarios involving tight coordination, where an operator seeks a dead robot in order to assist it. Extensive experiments with 25 human operators show that this new technique is superior to existing methods, in terms of reducing the time to locate the dead robot. We also show that the new method has much more consistent performance across different operators.